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Tamper Detection in Industrial Sensors: An Approach Based on Anomaly Detection

The Industrial Revolution 4.0 has catapulted the integration of advanced technologies in industrial operations, where interconnected systems rely heavily on sensor information. However, this dependency has revealed an essential vulnerability: Sabotaging these sensors can lead to costly and dangerous...

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Detalles Bibliográficos
Autores principales: Villegas-Ch, William, Govea, Jaime, Jaramillo-Alcazar, Angel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10650466/
https://www.ncbi.nlm.nih.gov/pubmed/37960607
http://dx.doi.org/10.3390/s23218908
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author Villegas-Ch, William
Govea, Jaime
Jaramillo-Alcazar, Angel
author_facet Villegas-Ch, William
Govea, Jaime
Jaramillo-Alcazar, Angel
author_sort Villegas-Ch, William
collection PubMed
description The Industrial Revolution 4.0 has catapulted the integration of advanced technologies in industrial operations, where interconnected systems rely heavily on sensor information. However, this dependency has revealed an essential vulnerability: Sabotaging these sensors can lead to costly and dangerous interruptions in the production chain. To address this threat, we introduce an innovative methodological approach focused on developing an anomaly detection algorithm specifically designed to track manipulations in industrial sensors. Through a series of meticulous tests in an industrial environment, we validate the robustness and accuracy of our proposal. What distinguishes this study is its unique adaptability to various sensor conditions, achieving high detection accuracy and prompt response. Our algorithm demonstrates superiority in accuracy and sensitivity compared to previously established methodologies. Beyond detection, we incorporate a proactive alert and response system, guaranteeing timely action against detected anomalies. This work offers a tangible solution to a growing challenge. It lays the foundation for strengthening security in industrial systems of the digital age, harmonizing efficiency with protection in the Industry 4.0 landscape.
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spelling pubmed-106504662023-11-02 Tamper Detection in Industrial Sensors: An Approach Based on Anomaly Detection Villegas-Ch, William Govea, Jaime Jaramillo-Alcazar, Angel Sensors (Basel) Article The Industrial Revolution 4.0 has catapulted the integration of advanced technologies in industrial operations, where interconnected systems rely heavily on sensor information. However, this dependency has revealed an essential vulnerability: Sabotaging these sensors can lead to costly and dangerous interruptions in the production chain. To address this threat, we introduce an innovative methodological approach focused on developing an anomaly detection algorithm specifically designed to track manipulations in industrial sensors. Through a series of meticulous tests in an industrial environment, we validate the robustness and accuracy of our proposal. What distinguishes this study is its unique adaptability to various sensor conditions, achieving high detection accuracy and prompt response. Our algorithm demonstrates superiority in accuracy and sensitivity compared to previously established methodologies. Beyond detection, we incorporate a proactive alert and response system, guaranteeing timely action against detected anomalies. This work offers a tangible solution to a growing challenge. It lays the foundation for strengthening security in industrial systems of the digital age, harmonizing efficiency with protection in the Industry 4.0 landscape. MDPI 2023-11-02 /pmc/articles/PMC10650466/ /pubmed/37960607 http://dx.doi.org/10.3390/s23218908 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Villegas-Ch, William
Govea, Jaime
Jaramillo-Alcazar, Angel
Tamper Detection in Industrial Sensors: An Approach Based on Anomaly Detection
title Tamper Detection in Industrial Sensors: An Approach Based on Anomaly Detection
title_full Tamper Detection in Industrial Sensors: An Approach Based on Anomaly Detection
title_fullStr Tamper Detection in Industrial Sensors: An Approach Based on Anomaly Detection
title_full_unstemmed Tamper Detection in Industrial Sensors: An Approach Based on Anomaly Detection
title_short Tamper Detection in Industrial Sensors: An Approach Based on Anomaly Detection
title_sort tamper detection in industrial sensors: an approach based on anomaly detection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10650466/
https://www.ncbi.nlm.nih.gov/pubmed/37960607
http://dx.doi.org/10.3390/s23218908
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